AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data

doi:10.1109/TCI.2022.3155379

	AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data
	Mengjie Guo1 ; Hengrong Lan1,2,3 ; Changchun Yang1 ; Jiang Liu 4,5; Fei Gao1,6
	2022
发表期刊	IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING (IF:4.2[JCR-2023],4.7[5-Year])
ISSN	2573-0436
卷号	8
发表状态	已发表
DOI	10.1109/TCI.2022.3155379
摘要	Photoacoustic (PA) imaging is a biomedical imaging modality capable of acquiring high-contrast images of optical absorption at depths much greater than traditional optical imaging techniques. However, practical instrumentation and geometry limit the number of available acoustic sensors surrounding the imaging target, which results in the sparsity of sensor data. Conventional PA image reconstruction methods give severe artifacts when they are applied directly to the sparse PA data. In this paper, we firstly propose to employ a novel signal processing method to make sparse PA raw data more suitable for the neural network, concurrently speeding up image reconstruction. Then we propose Attention Steered Network (AS-Net) for PA reconstruction with multi-feature fusion. AS-Net is validated on different datasets, including simulated photoacoustic data from fundus vasculature phantoms and experimental data from in vivo fish and mice. Notably, the method is also able to eliminate some artifacts present in the ground truth for in vivo data. Results demonstrated that our method provides superior reconstructions at a faster speed.
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收录类别	SCI ; SCIE ; EI
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/161470
专题	信息科学与技术学院信息科学与技术学院_PI研究组_高飞组信息科学与技术学院_硕士生信息科学与技术学院_博士生
作者单位	1.Hybrid Imaging System Laboratory, School of Information Science and Technology, ShanghaiTech University, Shanghai, China 2.Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China 3.University of Chinese Academy of Sciences, Beijing, China 4.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China 5.Cixi Institute of Biomedical Engineering, Chinese Academy of Sciences, Shanghai, China 6.Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, Shanghai, China
第一作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Mengjie Guo,Hengrong Lan,Changchun Yang,et al. AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data[J]. IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING,2022,8.
APA	Mengjie Guo,Hengrong Lan,Changchun Yang,Jiang Liu,&Fei Gao.(2022).AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data.IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING,8.
MLA	Mengjie Guo,et al."AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data".IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING 8(2022).